Improving resolution by image registration
CVGIP: Graphical Models and Image Processing
Example-Based Super-Resolution
IEEE Computer Graphics and Applications
Overcoming registration uncertainty in image super-resolution: maximize or marginalize?
EURASIP Journal on Advances in Signal Processing
Live-cell image enhancement using centre weighted median filter
ICCOMP'07 Proceedings of the 11th WSEAS International Conference on Computers
Computationally efficient algorithm for fuzzy rule-based enhancement on JPEG compressed color images
WSEAS Transactions on Signal Processing
WSEAS Transactions on Information Science and Applications
A locally tuned nonlinear technique for color image enhancement
WSEAS Transactions on Signal Processing
Bayesian Methods for Image Super-Resolution
The Computer Journal
A blind image restoration for out-of-focus blurred images using adaptive inverse filters
CIMMACS'05 Proceedings of the 4th WSEAS international conference on Computational intelligence, man-machine systems and cybernetics
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Image enhancement methods can be divided into two groups: the ones that use only one single image and the ones that rely on specific training set or use multiple images. In this paper an iterative algorithm, based on the quasi-Newton methods, is introduced with the objective to enhance resolution only by one single image. In the paper there will be compared results gained depending on the used method: nonlinear iterative algorithm vs. filtering algorithm with EMD. Empirical Mode Decomposition can be treated as filtering procedure for image enhancement.